Title:

Authors: Isabella C. Richmond¹*, Kayleigh Hutt-Taylor^1,2, Lauren Bianco¹, Antonia Vieira Zanella³, François Bérubé⁴, Paola Faddoul⁴, Kelly Vu⁴, Étienne Perreault-Mandeville⁵, Patrick Boivin⁶, Danielle Dagenais⁶, Nathalie Boucher⁵, Thi Thanh Hiên Pham⁴, Carly D. Ziter¹

1 Department of Biology, Concordia University, Montreal Canada, H4B 1R6

2 Tree Canada

3 Department of Geography, Federal University of Paraná, Paraná Brazil,

4 Département d’études urbaines et touristiques, Université du Québec à Montréal, Montreal Canada,

5 Organisme Respire

6 École d’urbanisme et d’architecture de paysage, Université de Montréal, Montreal Canada

* isabella.richmond@mail.concordia.ca

Prior Predictive Checks

Prior predictive checks are used to ensure that the values selected for priors for our models allow a biologically reasonable range of values. For numeric predictor variables, we simulate predictive draws for prior only models and visualize the slope/intercept of the values. We then do a “posterior predictive check” but with the prior only model, to see if the data is captured in the priors. Note that all data is scaled and centered in these data.

For Trois-Rivieres, there is only a categorical predictor variable. Therefore, only the posterior predictive check is presented.

Model 1a: Canopy cover in Villeray-Saint Michel-Parc Extension (VSMPE)

Model 1b: Canopy cover in Trois-Rivieres (TR)

Model 2: Firefly presence in VSMPE

Model 3a: Species richness in VSMPE

Model 3b: Species richness in TR

Model 4a: Functional richness in VSMPE

Model 4b: Functional richness in TR

Model 5a: Vegetative complexity in VSMPE

Model 5b: Vegetative complexity in TR

Model 6a: Proportion native trees in VSMPE

Model 6b: Proportion native trees in TR

Model 7a: Proportion invasive trees in VSMPE

Model 7b: Proportion invasive trees in TR